vdaas/vald
Vald. A Highly Scalable Distributed Vector Search Engine observed · 2026-08-28
Health v2 · maintenance only
91/100
- Activity 99
- Release rhythm 75
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 123.0
- age_days: 2614
- days_rel: 7
- days_push: 7
- n_releases_24m: 5
Adoption not part of the score
1718 stars · 95 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Vald is a highly scalable, distributed approximate nearest neighbor (ANN) dense vector search engine built on cloud-native architecture and the NGT algorithm. It runs on Kubernetes with automatic vector indexing, index backup, replication, and horizontal scaling designed for searching billions of feature vectors.
Use cases
- search billions of vectors for nearest neighbors
- build an image similarity search service
- power semantic text search with BERT embeddings
- deploy a scalable vector database on Kubernetes
- recommend similar products based on embeddings
- deduplicate images or videos by vector similarity
- back up and replicate vector indexes for disaster recovery
- query a vector search engine via gRPC or REST
When to choose
- you need a distributed, horizontally scalable ANN engine for billions of vectors
- your infrastructure is Kubernetes-based and you want cloud-native deployment via Helm
- you need automatic indexing, backup, and replica rebalancing without stop-the-world indexing
- you want gRPC and REST APIs with official Go, Java, Python, and Node.js SDKs
When to avoid
- you don't run Kubernetes and just need a simple embedded vector store
- your dataset is small enough for a single-node library like FAISS or Annoy
- you need a fully managed vector database service rather than self-hosted infrastructure
- you want a lightweight in-process ANN library instead of a distributed microservice cluster
Facets
service · maturity active
vector-database search-engine rpc deployment microservices sdk machine-learning databases cloud-computing microservices computer-vision go cloud self-hosted approximate-nearest-neighbor ann ngt vector-search similarity-search helm-chart grpc-api distributed-indexing image-search cncf-landscape search containers natural-language-processing kubernetes docker web-server
9 sources
- readme: https://github.com/vdaas/vald · fetched 2026-08-28 · 76ed7d73a2c8
- homepage: https://vald.vdaas.org · fetched 2026-08-29 · 69fd9055f24b
- site_page: https://vald.vdaas.org/docs/overview/about-vald · fetched 2026-08-29 · 756035ec6df1
- site_page: https://vald.vdaas.org/docs/tutorial/get-started · fetched 2026-08-29 · 84ef8c1e17ed
- site_page: https://vald.vdaas.org/docs/user-guides/sdks · fetched 2026-08-29 · a14c6565b4d3
- site_page: https://vald.vdaas.org/docs · fetched 2026-08-29 · 3aa699343d55
- site_page: https://vald.vdaas.org//docs/overview/architecture · fetched 2026-08-29 · 008ddcccf562
- site_page: https://vald.vdaas.org//docs/usecase/usage-example · fetched 2026-08-29 · fb05dfc9f25e
- site_page: https://vald.vdaas.org//docs/user-guides/configuration · fetched 2026-08-29 · 1b4b4a025ec2
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| vdaas/vald | main | 91 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem